Principal Data Engineer / ITS Operational Analytics

Hartford HealthCare Corp.•Newington, CT

About The Position

The Principal Data Engineer drives the strategic design, development, and optimization of Hartford HealthCare’s advanced data infrastructure. The role architects and develops data solutions that support reliable, high-performance analytics, data science initiatives, and digital transformation across the organization. The Principal Data Engineer works with cross-functional teams, leads the engineering team, and helps shape long-term data strategy while ensuring adherence to data governance, privacy, and security best practices. The position oversees scalable, resilient, and secure cloud-based and on-premises data pipelines; enterprise data architecture, models, ETL pipelines, and warehouses; and initiatives involving data lakehouse, data mesh, real-time streaming, serverless architectures, and machine learning integration. It collaborates with data scientists, data governance teams, clinical informatics, IT leadership, and organizational leaders to align architecture and technical strategy with organizational goals and business priorities. The role ensures compliance with HHC governance frameworks and healthcare regulations, including HIPAA and HITECH, and implements security, privacy, and audit controls for sensitive healthcare information. It also mentors and guides data engineers, promotes agile, DevOps, data version control, and automation practices, and develops technical roadmaps that anticipate future needs and scale data systems proactively.

Requirements

Bachelor’s degree in computer science, engineering, mathematics, or a related quantitative field.
At least 8 years of hands-on data software development experience, including cloud-native architectures; GCP is preferred.
At least 8 years of experience with programming languages such as Python, SQL, and Java.
At least 8 years of experience with specialized data architecture, such as data lake, lakehouse, data fabric, or data mesh.
At least 8 years of experience with ETL design, data modeling, and building robust data pipelines.
Advanced experience with cloud-based data engineering on GCP, AWS, or Azure.
Proactive, self-motivated approach and commitment to continuous learning and staying current with best practices, new features, and emerging technologies.
Ability to drive strategy, align technical solutions with business needs, and manage day-to-day operations across cross-functional teams.
Strong leadership, mentoring, and project management experience.
Time and project management skills.
Demonstrated verbal and written communication skills and in-person and virtual presentation skills.
In-depth knowledge of healthcare or healthcare system data.

Nice To Haves

Master’s degree in computer science, healthcare administration, or a related field.
10 or more years of experience in data software development, including building data and digital platforms.
10 or more years of experience with programming languages such as Python, SQL, and Java.
Experience with healthcare data standards such as FHIR and HL7 and with clinical systems.
10 or more years of experience with ETL design, data modeling, and building robust data pipelines.
7 or more years working with modern data governance, privacy frameworks, and healthcare compliance such as HIPAA.

Responsibilities

Design and oversee scalable, resilient, secure cloud-based and on-premises data pipelines for complex, large-scale data from multiple sources.
Drive strategic initiatives involving data lakehouse, data mesh, and other advanced data architectures.
Ensure high-performance data integration for enterprise reporting, AI-driven analytics, and digital health innovation.
Lead the design of enterprise-wide data architecture frameworks, including data models, ETL pipelines, and data warehouses.
Research and experiment with technologies such as real-time streaming, serverless architectures, and machine learning integration.
Collaborate with data scientists, data governance teams, clinical informatics, and IT leadership to align data architecture with organizational goals.
Partner with leadership to define long-term data strategies and align technical plans with business priorities.
Ensure data engineering solutions adhere to HHC data governance frameworks and comply with HIPAA, HITECH, and other healthcare regulations.
Implement automated data security and privacy controls and audit trails to protect sensitive healthcare information.
Lead, mentor, and provide technical guidance to junior and senior data engineers.
Promote agile development, DevOps, data version control, and automation best practices across the data engineering team.
Lead experimentation with data platforms, tools, and approaches to enhance organizational data capabilities.
Create technical roadmaps for data initiatives, anticipating future needs and proactively scaling systems.